AUTHOR = {Xu, Wenjia and Xian, Yongqin and Wang, Jiuniu and Schiele, Bernt and Akata, Zeynep}, LANGUAGE = {eng}, ISSN = {0920-5691}, DOI = {10.1007/s11263-022-01613-9}, PUBLISHER = {Springer}, ADDRESS [...] AUTHOR = {Xu, Wenjia and Xian, Yongqin and Wang, Jiuniu and Schiele, Bernt and Akata, Zeynep}, LANGUAGE = {eng}, ISBN = {9781713829546}, PUBLISHER = {Curran Associates, Inc.}, YEAR = {2020}, BOOKTITLE
Perception}, AUTHOR = {Li, Wenbin and Leonardis, Ale{\v s} and Bohg, Jeannette and Fritz, Mario}, LANGUAGE = {eng}, URL = {http://arxiv.org/abs/1904.09860}, EPRINT = {1904.09860}, EPRINTTYPE = {arXiv}, YEAR [...] and Shetty, Rakshith and Li, Wenbin and Malinowski, Mateusz and Fritz, Mario and Leonardis, Ales}, LANGUAGE = {eng}, ISBN = {978-3-030-11008-6}, DOI = {10.1007/978-3-030-11009-3_32}, PUBLISHER = {Springer} [...] binphd2018, TITLE = {From Perception over Anticipation to Manipulation}, AUTHOR = {Li, Wenbin}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-ds-271561}, DOI = {10.22028/D291-27156}, SCHOOL = {Un
Web Service in a commercial scenario, have a look at the Ambiverse Natural Language Understanding API . The Natural Language Understanding API provides a faster, more accurate, and commercially supported
and model the mutual interaction between: the stance (i.e., support or refute) of the sources, the language style of the articles, the reliability of the sources, and the claim’s temporal footprint on the
Group Computational Biology RG1 Automation of Logic RG2 Network and Cloud Systems RG3 Multimodal Language Processing Home Institute Mission Address Executive Board Scientific Members of MPG Scientific Advisory [...] Group Computational Biology RG1 Automation of Logic RG2 Network and Cloud Systems RG3 Multimodal Language Processing Publications Algorithms & Complexity Computer Vision and Machine Learning Internet A
{M}ulti-Modal Language Model of Egocentric Motions}, AUTHOR = {Hong, Fangzhou and Guzov, Vladimir and Kim, Hyo Jin and Ye, Yuting and Newcombe, Richard and Liu, Ziwei and Ma, Lingni}, LANGUAGE = {eng}, PUBLISHER [...] Fangzhou and Pons-Moll, Gerard and Newcombe, Richard and Liu, C. Karen and Ye, Yuting and Ma, Lingni}, LANGUAGE = {eng}, PUBLISHER = {IEEE}, YEAR = {2025}, PUBLREMARK = {Accepted}, MARGINALMARK = {$\bullet$} [...] and Guzov, Vladimir and Dhamo, Helisa and P{\'e}rez Pellitero, Eduardo and Pons-Moll, Gerard}, LANGUAGE = {eng}, PUBLISHER = {IEEE}, YEAR = {2025}, PUBLREMARK = {Accepted}, MARGINALMARK = {$\bullet$}
Vision and Machine Learning Research Vision and Language Visual Turing Challenge Visual Turing Challenge Mateusz Malinowski and Mario Fritz Challenge As language and visual understanding by machines progresses [...] choices required in the previous work. The network has successfully learnt patterns that occur in language, significantly improving over the previous work. Moreover, we extend the WUPS scores to handle multiple [...] Diverse Captions with Adversarial Training Xplore-M-Ego: Contextual Media Retrieval Using Natural Language Queries Visual Turing Challenge Learning Spatial Relations TACoS Multi-Level Corpus MPII Movie
Computer Vision and Machine Learning Research Vision and Language Vision and Language Xplore-M-Ego: Contextual Media Retrieval Using Natural Language Queries The widespread integration of cameras in hand-held [...] to query a database of contextualised images using spatio-temporal natural language queries. Visual Turing Challenge As language and visual understanding by machines progresses rapidly, we are observing [...] how it improves image retrieval and annotations tasks involving spatial language. Due to the complexity of the spatial language, we argue for a learning-based approach that acquires a representation of
a target object, namely by employing language referring expressions. Besides being a more practical and natural way of pointing out a target object, using language specifications can help to avoid drift [...] training set that is closer to the target domain is more effective. Video Object Segmentation with Language Referring Expressions Most state-of-the-art semi-supervised video object segmentation methods rely [...] system more robust to complex dynamics and appearance variations. Leveraging recent advances of language grounding models designed for images, we propose an approach to extend them to video data, ensuring
were fixed, and not programmable. Later, the P4 language was introduced to bring programmability to the data plane as well. P4 is a domain specific language with multiple abstractions for packet processing
